6 resultados para Subgrid Scale Model

em CORA - Cork Open Research Archive - University College Cork - Ireland


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High-permittivity ("high-k") dielectric materials are used in the transistor gate stack in integrated circuits. As the thickness of silicon oxide dielectric reduces below 2 nm with continued downscaling, the leakage current because of tunnelling increases, leading to high power consumption and reduced device reliability. Hence, research concentrates on finding materials with high dielectric constant that can be easily integrated into a manufacturing process and show the desired properties as a thin film. Atomic layer deposition (ALD) is used practically to deposit high-k materials like HfO2, ZrO2, and Al2O3 as gate oxides. ALD is a technique for producing conformal layers of material with nanometer-scale thickness, used commercially in non-planar electronics and increasingly in other areas of science and technology. ALD is a type of chemical vapor deposition that depends on self-limiting surface chemistry. In ALD, gaseous precursors are allowed individually into the reactor chamber in alternating pulses. Between each pulse, inert gas is admitted to prevent gas phase reactions. This thesis provides a profound understanding of the ALD of oxides such as HfO2, showing how the chemistry affects the properties of the deposited film. Using multi-scale modelling of ALD, the kinetics of reactions at the growing surface is connected to experimental data. In this thesis, we use density functional theory (DFT) method to simulate more realistic models for the growth of HfO2 from Hf(N(CH3)2)4/H2O and HfCl4/H2O and for Al2O3 from Al(CH3)3/H2O.Three major breakthroughs are discovered. First, a new reaction pathway, ’multiple proton diffusion’, is proposed for the growth of HfO2 from Hf(N(CH3)2)4/H2O.1 As a second major breakthrough, a ’cooperative’ action between adsorbed precursors is shown to play an important role in ALD. By this we mean that previously-inert fragments can become reactive once sufficient molecules adsorb in their neighbourhood during either precursor pulse. As a third breakthrough, the ALD of HfO2 from Hf(N(CH3)2)4 and H2O is implemented for the first time into 3D on-lattice kinetic Monte-Carlo (KMC).2 In this integrated approach (DFT+KMC), retaining the accuracy of the atomistic model in the higher-scale model leads to remarkable breakthroughs in our understanding. The resulting atomistic model allows direct comparison with experimental techniques such as X-ray photoelectron spectroscopy and quartz crystal microbalance.

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A novel numerical model of a Bent Backwards Duct Buoy (BBDB) Oscillating Water Column (OWC) Wave Energy Converter was created based on existing isolated numerical models of the different energy conversion systems utilised by an OWC. The novel aspect of this numerical model is that it incorporates the interdependencies of the different power conversion systems rather than modelling each system individually. This was achieved by accounting for the dynamic aerodynamic damping caused by the changing turbine rotational velocity by recalculating the turbine damping for each simulation sample and applying it via a feedback loop. The accuracy of the model was validated using experimental data collected during the Components for Ocean Renewable Energy Systems (CORES) EU FP-7 project that was tested in Galway Bay, Ireland. During the verification process, it was discovered that the model could also be applied as a valuable tool when troubleshooting device performance. A new turbine was developed and added to a full scale model after being investigated using Computational Fluid Dynamics. The energy storage capacity of the impulse turbine was investigated by modelling the turbine with both high and low inertia and applying three turbine control theories to the turbine using the full scale model. A single Maximum Power Point Tracking algorithm was applied to the low-inertia turbine, while both a fixed and dynamic control algorithm was applied to the high-inertia turbine. These results suggest that the highinertia turbine could be used as a flywheel energy storage device that could help minimize output power variation despite the low operating speed of the impulse turbine. This research identified the importance of applying dynamic turbine damping to a BBDB OWC numerical model, revealed additional value of the model as a device troubleshooting tool, and found that an impulse turbine could be applied as an energy storage system.

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The human body is colonized by an enormous population of bacteria (microbiota) that provides the host with coding capacity and metabolic activities. Among the human gut microbiota are health-promoting indigenous species (probiotic bacteria) that are commonly consumed as live dietary supplements. Recent genomics-based studies (probiogenomics) are starting to provide insights into how probiotic bacteria sense and adapt to the gastrointestinal tract environment. In this Review, we discuss the application of probiogenomics in the elucidation of the molecular basis of probiosis using the well-recognized model probiotic bacteria genera Bifidobacterium and Lactobacillus as examples.

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Evaluation of temperature distribution in cold rooms is an important consideration in the design of food storage solutions. Two common approaches used in both industry and academia to address this question are the deployment of wireless sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld evaluation of temperature distribution in a cold room, both approaches have their limitations. For wireless sensors, it is economically unfeasible to carry out large-scale deployment (to obtain a high resolution of temperature distribution); while with CFD modelling, it is usually not accurate enough to get a reliable result. In this paper, we propose a model-based framework which combines the wireless sensors technique with CFD modelling technique together to achieve a satisfactory trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms. A case study is presented to demonstrate the usability of the framework.

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The measurement of users’ attitudes towards and confidence with using the Internet is an important yet poorly researched topic. Previous research has encountered issues that serve to obfuscate rather than clarify. Such issues include a lack of distinction between the terms ‘attitude’ and ‘self-efficacy’, the absence of a theoretical framework to measure each concept, and failure to follow well-established techniques for the measurement of both attitude and self-efficacy. Thus, the primary aim of this research was to develop two statistically reliable scales which independently measure attitudes towards the Internet and Internet self-efficacy. This research addressed the outlined issues by applying appropriate theoretical frameworks to each of the constructs under investigation. First, the well-known three component (affect, behaviour, cognition) model of attitudes was applied to previous Internet attitude statements. The scale was distributed to four large samples of participants. Exploratory factor analyses revealed four underlying factors in the scale: Internet Affect, Internet Exhilaration, Social Benefit of the Internet and Internet Detriment. The final scale contains 21 items, demonstrates excellent reliability and achieved excellent model fit in the confirmatory factor analysis. Second, Bandura’s (1997) model of self-efficacy was followed to develop a reliable measure of Internet self-efficacy. Data collected as part of this research suggests that there are ten main activities which individuals can carry out on the Internet. Preliminary analyses suggested that self-efficacy is confounded with previous experience; thus, individuals were invited to indicate how frequently they performed the listed Internet tasks in addition to rating their feelings of self-efficacy for each task. The scale was distributed to a sample of 841 participants. Results from the analyses suggest that the more frequently an individual performs an activity on the Internet, the higher their self-efficacy score for that activity. This suggests that frequency of use ought to be taken into account in individual’s self-efficacy scores to obtain a ‘true’ self-efficacy score for the individual. Thus, a formula was devised to incorporate participants’ previous experience of Internet tasks in their Internet self-efficacy scores. This formula was then used to obtain an overall Internet self-efficacy score for participants. Following the development of both scales, gender and age differences were explored in Internet attitudes and Internet self-efficacy scores. The analyses indicated that there were no gender differences between groups for Internet attitude or Internet self-efficacy scores. However, age group differences were identified for both attitudes and self-efficacy. Individuals aged 25-34 years achieved the highest scores on both the Internet attitude and Internet self-efficacy measures. Internet attitude and self-efficacy scores tended to decrease with age with older participants achieving lower scores on both measures than younger participants. It was also found that the more exposure individuals had to the Internet, the higher their Internet attitude and Internet self-efficacy scores. Examination of the relationship between attitude and self-efficacy found a significantly positive relationship between the two measures suggesting that the two constructs are related. Implication of such findings and directions for future research are outlined in detail in the Discussion section of this thesis.

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Due to growing concerns regarding the anthropogenic interference with the climate system, countries across the world are being challenged to develop effective strategies to mitigate climate change by reducing or preventing greenhouse gas (GHG) emissions. The European Union (EU) is committed to contribute to this challenge by setting a number of climate and energy targets for the years 2020, 2030 and 2050 and then agreeing effort sharing amongst Member States. This thesis focus on one Member State, Ireland, which faces specific challenges and is not on track to meet the targets agreed to date. Before this work commenced, there were no projections of energy demand or supply for Ireland beyond 2020. This thesis uses techno-economic energy modelling instruments to address this knowledge gap. It builds and compares robust, comprehensive policy scenarios, providing a means of assessing the implications of different future energy and emissions pathways for the Irish economy, Ireland’s energy mix and the environment. A central focus of this thesis is to explore the dynamics of the energy system moving towards a low carbon economy. This thesis develops an energy systems model (the Irish TIMES model) to assess the implications of a range of energy and climate policy targets and target years. The thesis also compares the results generated from the least cost scenarios with official projections and target pathways and provides useful metrics and indications to identify key drivers and to support both policy makers and stakeholder in identifying cost optimal strategies. The thesis also extends the functionality of energy system modelling by developing and applying new methodologies to provide additional insights with a focus on particular issues that emerge from the scenario analysis carried out. Firstly, the thesis develops a methodology for soft-linking an energy systems model (Irish TIMES) with a power systems model (PLEXOS) to improve the interpretation of the electricity sector results in the energy system model. The soft-linking enables higher temporal resolution and improved characterisation of power plants and power system operation Secondly, the thesis develops a methodology for the integration of agriculture and energy systems modelling to enable coherent economy wide climate mitigation scenario analysis. This provides a very useful starting point for considering the trade-offs between the energy system and agriculture in the context of a low carbon economy and for enabling analysis of land-use competition. Three specific time scale perspectives are examined in this thesis (2020, 2030, 2050), aligning with key policy target time horizons. The results indicate that Ireland’s short term mandatory emissions reduction target will not be achieved without a significant reassessment of renewable energy policy and that the current dominant policy focus on wind-generated electricity is misplaced. In the medium to long term, the results suggest that energy efficiency is the first cost effective measure to deliver emissions reduction; biomass and biofuels are likely to be the most significant fuel source for Ireland in the context of a low carbon future prompting the need for a detailed assessment of possible implications for sustainability and competition with the agri-food sectors; significant changes are required in infrastructure to deliver deep emissions reductions (to enable the electrification of heat and transport, to accommodate carbon capture and storage facilities (CCS) and for biofuels); competition between energy and agriculture for land-use will become a key issue. The purpose of this thesis is to increase the evidence-based underpinning energy and climate policy decisions in Ireland. The methodology is replicable in other Member States.